MétaCan
Menu
Back to cohort
Record W4415486662 · doi:10.1139/cjp-2025-0086

The instrumentation suite for the HBS-I

2025· article· en· W4415486662 on OpenAlexvenueno aff
Klaus Lieutenant, Eric Mauerhofer, Ulrich Rücker, Norberto Schmidt, Johannes Baggemann, Thomas Gutberlet, Paul Zakalek, J. Voigt

Bibliographic record

VenueCanadian Journal of Physics · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle Detector Development and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsNeutronNeutron sourceNeutron scatteringNeutron time-of-flight scatteringSuiteNeutron radiationNeutron detectionInstrumentation (computer programming)

Abstract

fetched live from OpenAlex

High-Current Accelerator-driven Neutron Sources (HiCANS) are a promising new type of neutron sources, which can offer pulsed neutron beams with performance comparable to today’s existing research neutron sources. The Jülich Centre for Neutron Science JCNS at Forschungszentrum Jülich aims to realize a first HiCANS with the HBS-I neutron source featuring a proton beam energy of 20 MeV, a peak current of 100 mA, and a flexible frequency and duty cycle scheme. The HBS-I will allow to exploit the potential of these innovative neutron sources for a broad range of scientific and technological applications. The target station will be located in an experimental area on the campus in Jülich and host a suite of five instruments. A diffractometer, a small angle scattering instrument, and a neutron reflectometer address the most demanded scattering applications, while neutron imaging and prompt gamma neutron activation analysis cover the need of user communities such as engineering or cultural heritage research. This paper describes the preliminary layout of the HBS-I neutron source and the five instruments planned.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.167
Threshold uncertainty score0.557

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0030.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.1670.068

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.244
Teacher spread0.231 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of PhysicsSame topicParticle Detector Development and PerformanceFrench-language works237,207